A multi-input radio frequency power amplifier is a power amplifier that has two or more radio frequency signal input ends and a single output end. Compared with a conventional single-input single-output radio frequency power amplifier, the multi-input radio frequency power amplifier has better performance. In addition, a relationship between amplitude and a phase of each input signal of the multi-input radio frequency power amplifier can be adjusted. Therefore, the multi-input radio frequency power amplifier has better performance, and the multi-input radio frequency power amplifier attracts more attention.
A conventional transmitter using a multi-input power amplifier requires at least two complete radio frequency small-signal links. In this case, a quantity of small-signal paths increases in the transmitter, and a structure of the transmitter becomes complex. To simplify a structure of a transmitter, a radio frequency signal decomposition solution is generally used in a current transmitter. The structure of the transmitter in which the radio frequency signal decomposition solution is used may be shown in FIG. 1: A signal component splitting module 15 receives a signal output by a quadrature modulator 14, decomposes the received signal into two channels of signals, and outputs the signals into two drive amplifiers 16. The transmitter shown in FIG. 1 further includes a digital predistortion module 11, a quadrature modulation compensation module 12, a digital-to-analog conversion module 13, a radio frequency power amplifier 17, a down-converter 18, and an analog-to-digital conversion module 19.
As shown in FIG. 2, the signal component splitting module includes an envelope detector 21, a quadrature signal splitter 22, a multiplier 23, and a curve fitting circuit 24. A design of the curve fitting circuit 24 is a key in the signal component splitting module, and a function of the curve fitting circuit is to convert an input signal represented by a real number into an output signal represented by a complex number. The curve fitting circuit implements mathematical computation by using a circuit. Therefore, an error is unavoidable, and this requires that a circuit structure features a particular tolerance.
A polynomial fitting method is generally used to implement the function of the curve fitting circuit. For example, a relationship between a signal x and a signal y is y=f(x). After the curve fitting circuit receives the signal x, the curve fitting circuit uses xn as a basis function to fit the relationship between the signal x and the signal y and obtains y=a*x5+b*x4+c*x3+d*x2+e*x1+f, so as to output the signal y, where basis functions are respectively x5, x4, x3, x2, x1, and x0, and a, b, c, d, e, and f are respectively coefficients of the basis functions.
When polynomial-fitting is directly used, the signal component splitting module implementing a radio frequency signal decomposition function needs to fit a relatively complex curve. Generally, a higher order polynomial needs to be used. In this case, a fitting result is very sensitive to a higher order term coefficient, that is, a higher order coefficient. In addition, because the higher order polynomial is used, the fitting result is also very sensitive to a quantization noise.
In conclusion, a curve that needs to be fit during radio frequency signal decomposition is relatively complex, and a higher order polynomial is generally used when a current polynomial fitting method is used. Therefore, a fitting result is not only very sensitive to a higher order term coefficient, but also very sensitive to a quantization noise.